Ideal Observer Computation by Use of Markov-Chain Monte Carlo With Generative Adversarial Networks-Reference-Cited by-同舟云学术

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Ideal Observer Computation by Use of Markov-Chain Monte Carlo With Generative Adversarial Networks

Published:2023-12 Issue:12 Volume:42 Page:3715-3724
ISSN:0278-0062
Container-title:IEEE Transactions on Medical Imaging
language:
Short-container-title:IEEE Trans. Med. Imaging

Author:

Zhou Weimin¹^ORCID,Villa Umberto²^ORCID,Anastasio Mark A.³^ORCID

Affiliation:

1. Global Institute of Future Technology, Shanghai Jiao Tong University, Shanghai, China

2. Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, TX, USA

3. Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, USA

Funder

NIH Awards

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Radiological and Ultrasound Technology,Software

Link

http://xplorestaging.ieee.org/ielx7/42/10336247/10216380.pdf?arnumber=10216380

Reference72 articles.

1. Channelized-ideal observer using Laguerre-Gauss channels in detection tasks involving non-Gaussian distributed lumpy backgrounds and a Gaussian signal

2. Inference from Iterative Simulation Using Multiple Sequences

3. Validating the use of channels to estimate the ideal linear observer

4. Berkeley advanced reconstruction toolbox;uecker;Proc Int Soc Mag Reson Med,2015

5. Efficient estimation of ideal-observer performance in classification tasks involving high-dimensional complex backgrounds

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